7.30.2015

Dr. Frances Ross at the IBM Thomas J Watson
Research Center. Photo credit: Chris Ramirez
for The New York Times

“Whiskers” have been recorded in natural ores
since the 1500s. These crystal formations indeed look like a cat’s whiskers, but
function as wires. And since Bell Labs in the 1960s began to grow whiskers deliberately
out of many different substances, materials scientists have been molding them
into everything from photovoltaic devices, transistors, sensors, solid state
lighting and batteries. At IBM Research, with colleagues from academia and the Brookhaven
National Laboratory, we have developed a way to make these structures grow in
an electron microscope. By recording the atoms self-assembling
to form the whiskers – renamed in modern fashion as nanowires – we hope to understand how they grow and how to tune the
growth conditions to build nano-devices.

The term nanowire describes any crystal that
is thin in diameter, down to tens of nanometers, but with a length maybe
hundreds or thousands of times greater. The material that the nanowire is made
of, and its exact dimensions, determine its performance. For example, how solar
energy is absorbed, in the case of photovoltaics. Or how lithium moves along a nanowire,
in the case of rechargeable batteries. And how magnetic fields arrange
themselves along its length, in the case of IBM’s racetrack
memory. The big bang in these tiny structures comes from the fact that at
nanoscale dimensions, even conventional materials can behave in remarkable and
unexpected ways.

One exciting opportunity for nanowires is as
building blocks for transistors in microelectronics. While getting to the 7
nanometer node is heroic, the lithographic process conventionally used to
define the circuits is ultimately limited. Using self-assembled nanowires as
the cores of the transistors can provide a pathway to smaller circuits, and
perhaps even new designs that need less power to perform computations.

Our experiments started with the goal of understanding
how the atoms spontaneously arrange themselves into the simplest sorts of nanowires,
those that are made up of only one material. We chose our favorite element,
silicon, the semiconductor that forms the basis of microelectronics. The nanowires
grow with the help of a catalyst. So, we start with a flat wafer of silicon, add
a couple of layers of gold atoms and heat until the gold and silicon react chemically
and form tiny liquid droplets. The reaction takes place at 370oC,
and results in something that looks a lot like a pane of glass covered by raindrops
– at the nano-scale.

A silicon nanowire at 5nm and 20nm.

The trick is then to flow disilane gas, which
contains silicon atoms, across the hot, droplet-covered silicon surface. When a
molecule touches the surface of the silicon wafer, it bounces off and nothing
changes. But when a molecule hits the surface of the gold droplet, it sticks
and breaks apart, and its silicon atoms enter the droplet. As more silicon
enters a droplet, the excess settles out as solid silicon beneath the droplet.
Think of gradually adding spoonfuls of sugar to your coffee: excess sugar eventually
settles at the bottom of the cup. In the case of the nanowires, the settling does
not form disordered sludge, but instead a perfect layer of silicon atoms. The
droplet stays at the top, and the nanowire keeps growing as long as we keep the
gas flowing. The photo shows a nanowire during growth: the liquid droplet,
labeled Au-Si, sits on top of the nanowire.

Watching this process in our electron
microscope, and later in a microscope at Brookhaven National Laboratory with a
high-speed (400 frames–per-second) movie camera, was an amazing experience. The
video below shows the nanowire and the droplet, where the rows of dots indicate
positions of silicon atoms in the nanowire. Layers of silicon atoms add onto
the nanowire beneath the liquid droplet.

Watch how a silicon nanowire self-assembles under a gold-silicon droplet,and grows around a nanocrystal of nickel disilicide

Droplet size determined the nanowire’s
diameter. Temperature determined how long, and how quickly, the nanowire grew. We
also tested other important semiconductors – germanium, gallium arsenide and
gallium phosphide – and showed that their nanowires grew in a similar way. This
finding helps us to understand how to build more complicated structures. So, we
watched what happened as we switched from one gas to another, and learned the
rules that govern which semiconductors could be stacked layer by layer, within a
single nanowire.

Because each layer has different electronic behavior, these
complicated nanowires could form versatile nano-devices. And it’s possible to grow even more
complicated nanowires.

Our most recent experiments show what happens
when we add metals, such as nickel or cobalt, to the catalytic droplet. Instead
of settling out as a flat layer, the metal forms a single nanocrystal that
floats in the droplet. Eventually this nanocrystal settles out, and we can grow
the nanowire around it. This sequence of events was completely unexpected to us
– imagine if you add that extra spoonful of sugar to your coffee and then find
a perfect cube of sugar floating in the liquid! Electron microscope videos help
us understand why the atoms assemble in this way, and how to control the
resulting nanowire to optimize the shape, size and position of the embedded
nanocrystals.

Self-assembling nanowires creates new
concepts for nanomaterials, helping us build structures that cannot be
fabricated using conventional techniques. The self-assembly process is still challenging
because every nanowire comes out slightly different – perhaps imperfect for use
in a device. We are not yet precise enough to exactly replicate the process across
an entire wafer, much less build reliable nano-devices. However, each step
forward, such as the nanowires with embedded nanocrystals, suggests new opportunities
for electronics and other applications.

Self-assembly will succeed when we can
harness the spontaneous behavior of atoms. That’s an exciting prospect. We need
to change our way of thinking to avoid the need for perfection, but still
control how the self-assembled structures behave under certain conditions –
allowing us to create wholly unique devices and capabilities.

7.28.2015

It's been 25 years since the Americans with Disabilities Act was signed into law. Organizations
should be creating a holistic strategy for embedding accessibility across the
entire enterprise - from processes, to product development, to education and
training. But it's often still decentralized,
and managed disparately across a business, often resulting in solutions
that, instead, create barriers to information and don’t meet mandated levels of compliance.

To help organizations
have better visibility and management over accessibility initiatives, IBM launched
the IBM AbilityLab Compliance System. The solution helps establish and
document accessibility standards compliance for all information and
communication technologies (ICT), such as employee systems, customer-facing
mobile and web applications, hardware, kiosks, and telecommunications.

Organizations can now
better manage accessibility with a self-service reporting system that records
and tracks ICT compliance over time as standards, techniques and tools change. The
system allows executives to get reports that can track the accessibility of
products and services across the organization. With business dynamics changing
rapidly enterprises can get a good view of long term trends on how accessibility
is impacting their overall business.

This system includes
leading industry accessibility checklists, an extensive library of education
and training modules, and a web assessment testing tool that examines and
provides recommendations on improving the usability of web applications by
ensuring compliance with accessibility standards, such as alternative text,
proper tabbing and keyboard navigation, and color contrast.

Finally, the new
solution includes a centralized process and business workflow that tracks
accessibility, assigns responsibility and enables a broad group of internal
stakeholders – beyond those who may manage ICT accessibility quality assurance (QA)
tools – to have access to detailed reporting and auditing capabilities. This
helps organizations prioritize resources, be more agile with product development,
and accurately respond to requirements from customers and employees.

As part of this
rollout, IBM is collaborating with Freedom Scientific to offer organizations a complete portfolio of enterprise accessibility training and eLearning to ensure that all employees –
designers, developers, testers, quality assurance, and program managers – are following best
practices in accessibility and are educated on current regulations and industry
standards.

7.27.2015

Scientists in Switzerland have kicked off a three-year project which uses a substance, similar to the silica gel desiccant packs often found in leather shoe boxes and electronics, to convert wasted heat from cloud data centers to cool air. The potential result, cloud data centers of the future might be able to cool themselves using their own waste heat.

The project is called THRIVE and it's goal is simple - to develop a heat pump powered by waste heat. If you have ever felt the hot air from an air conditioning unit or from the back of PC, this is waste heat. Waste heat can be very valuable and there is plenty of it coming from factories, power stations, data centers or other renewable sources such as solar power. It just needs to be harnessed and put to work efficiently.

A coated adsorber heat exchanger
tested at the Institute for Solar Technologies
at University of Applied Sciences Rapperswil.

Heat Pumps 101

Chances are you use a heat pump every day. They can be found in heating, ventilating, and air conditioning units to to convert environmental heat, the temperature of which lies between -5 and 15°C, into thermal heat for rooms or processes.

Traditional heat pumps draw warmth from the surroundings, such as from the earth or air, to vaporize a refrigerant in an evaporator. The vapor produced in the process rises into an electrically powered compressor, which condenses it and thus heats it up.

The vapor then turns back into liquid in an adjoining condenser and releases the heat into a heating cycle. This process can be used to produce both heat to air-condition rooms and cool air, like in a refrigerator.

Adsorption heat pump

A thermally powered adsorption heat pump works in a similar way – the major difference being that, in place of a compressor, it has an adsorption heat exchanger that uses heat at temperatures from 60°C as its driving energy instead of electricity.

During the so-called adsorption process, the adsorption heat exchanger adsorbs considerable amounts of vapor from the evaporator and compresses it inside the heat exchanger, thereby releasing heat. The refrigerant adsorbed beforehand is forced (desorbed) back out of the adsorption heat exchanger by the supply of driving heat from an external source.

The hot vapor released as a result turns back into liquid in the condenser and the corresponding condensation heat is released into the heating cycle. The adsorption heat pump can also be use to heat and cool.

These processes are supported by the desiccant or silca gel which will be filled in between the fins of the adsorber heat exchanger.

However, as the cooling or heat production takes place intermittently, at least two adsorption heat exchangers working in parallel are needed for it to run uninterrupted. Due to their low energy consumption, adsorption heat pumps achieve a much higher cooling or heat output in relation to the wattage used than conventional heat pumps.

In addition, pure water can be used as a coolant instead of refrigerants, which can sometimes be harmful for the environment. Another advantage of the technology is the fact that renewable heat sources can be used, such as solar-thermal systems, which typically generate temperatures of up to 90°C.

“Through the extensive use of the adsorption heat pumps we are looking to develop in THRIVE, it could theoretically be possible to reduce the electricity demand for heating and cooling purposes by up to 65% and the consumption of fossil fuels for heat production by up to 18% by 2040.” This would correspond to savings of around 1.8 million tons of CO2," says Dr. Bruno Michel, one of the THRIVE project leaders at IBM Research - Zurich.

Using a data center to heat and cool buildings

By using heat, the adsorption heat pump is the ideal solution for many interesting applications where conventional heat pumps don’t make any sense. It could, for instance, use the waste heat from future, actively cooled, concentrated photovoltaic plants or cloud data centers that are cooled with hot water to provide air-conditioning for offices or residential buildings.

The Aquasar computer system developed by IBM researchers in collaboration with ETH Zurich in 2010 is a pioneer of hot-water cooling for computer systems, which not only massively reduces the energy demand for cooling in computer centers, but also enables the reuse of waste heat.

For the IBM researchers, THRIVE is the next step to make this a reality. Hot water-cooled data centers could then practically cool themselves using their own waste heat.

”In the THRIVE project, we have a unique opportunity to
combine the latest findings from materials science, the technological
optimization of heat exchangers and the merging of system and plant
engineering from different disciplines,“ says Elimar Frank from the
Hochschule für Technik Rapperswil and co-leader of the THRIVE project.

7.22.2015

Editor's note: This article is by Léa Deleris, manager of Risk Management at IBM Research-Ireland. Additional contributions made by Charles Jochim, research staff member at IBM Research-Ireland.

Alice: `Would you tell me, please, which way I ought to go from
here?'

Cheshire Cat: `That depends a good deal on where you want to get to.'

Alice: `I don't much care where—‘

Cheshire Cat: `Then it doesn't matter which way you go.’

Alice: ‘So long as I get somewhere.’

Cheshire Cat: `Oh, you're sure to do
that, if you only walk long enough.'

This
dilemma, and Stanford’s Decision Analysis Professor Dr. Rob Howard, who presented
the Alice in Wonderland
concept of indifference in a lecture, inspired me to study how mathematics can
apply to the risk, uncertainty, and personal preferences that influence the
decisions we make every day, about everything. What Alice and the Cheshire Cat
so eloquently illustrate is that preferences are not as obvious as they may
seem. I wanted to know, as a PhD student sitting among my fellow classmates,
could natural language processing and cognitive computing be applied to web
applications that could in turn, help us make more logical decisions?

Fast
forward to today, and from student to IBM research scientist, and I’m applying
artificial intelligence to our human intelligence – and how we can debate with
machines to help us make good decisions when facing uncertainty. Here’s how I
explained it to a TEDxParis
audience in February.

Now
my team in Dublin is using machines to help medical professionals make more
rational decisions. The tool we developed, called MedicalRecap,
extracts information from PubMed’s 24
million online citations to create a risk model for doctors.

MedicalRecap’s semantic module allows doctors to
cluster the extracted terms (variables of the risk model) by
grouping similar or related terms into concepts. It also has an aggregation
module, which allows the user to combine the extracted dependence and probability
statements into a dependence graph, also known as a Bayesian network.

Imagine
an instance of a doctor needing to understand the role of tea and coffee
consumption on the incidence of endometrial cancer. Currently, doctors would
address this task manually by searching for relevant papers, reading them,
taking notes (by hand or copy-pasting on a spreadsheet), and aggregating this
data.

MedicalRecap,
instead, presents extracted and aggregated data in an intuitive graphical
format, providing a way for the user to trace back through the summarised
information, to the original input. The tool also allows users to edit the
output of the algorithms if they encounter an error, which is fed back into the
system to improve its knowledge and performance over time.

MedicalRecap
also relies on the doctor's expertise, so ideally, errors are reduced by
combining the doctor's knowledge with the inferences the tool makes in finding
dependency relationships. The assumption is
that the doctor does not have all the input required, but is exploring the
space. The tool helps the practitioner look for answers, but does not provide
them. Ideally, it will reach the same conclusions that the doctor already has
made so that he or she will trust the system more.

We also want MedicalRecap to provide evidence for new conclusions to be
drawn. For example, if the doctor sees that coffee consumption is linked to
some cancers, which she already knew, the tool could show that in fact this is
primarily for certain populations, which she didn't know.

As similar as it
may sound, MedicalRecap is different to IBM Watson Health.
Our tool is a web-based GUI focused only on published medical literature and is
not designed for personalized medicine, but instead to make more global inferences
between diseases and related risk factors. But like Watson, MedicalRecap’s
Extractor, Clusterer, and Aggregator services are available on IBM’s SoftLayer cloud infrastructure
as a service.

Our risk information extraction models, like in MedicalRecap, can be applied
to other domains. In the future, oil and gas experts could use the tool to extract
information from academic papers about factors influencing reservoir capacity
and shape. As long as
we have the main ingredient of a large body of literature related to a profession
or domain, our decision support system tool might even be able to offer
Alice somewhere to go, no matter how unsure she is.

7.16.2015

Arriving at IBM Research - Africa in Nairobi, Kenya, I
knew this was going to be my dream job. As a research scientist, you see the
continent of Africa as a huge breeding ground for innovation, and an
opportunity to make a tangible impact. As most residents and visitors to Nairobi would say, the bustle of the city paired with a flourishing tech and innovation scene provides an experience unmatched.

Unfortunately, those same residents and visitors are
severely impacted by a tense traffic issue that challenges the city's
infrastructure. In fact, the Nairobi government estimates that traffic jams and
roadway problems result in a loss of more than $500,000 USD every day, when measuring
lost productivity, fuel consumption, accidents and fatalities and emergency
response.

My role at the Research lab in Nairobi focuses on
mobility: environment, water, roadways, and the overall city ecosystem. In a
meeting this month with the Executive Committee Member, Nairobi City County Evans Ondieki, my team learned
that, in parallel to the imminent traffic issue, the city's waste management
system was operating inefficiently: Nairobi's 3 million citizens
generate 2,200 tons of waste each day, but less than half is collected.

In fact,
the city's waste management truck fleet was increased by 300 percent to
accommodate the overwhelming amount of waste generated across the city and
countryside, but the current systems are hand-written and riddled with
inconsistencies like equipment failures, manual reporting that takes a day to
process, and traffic jams that slow the pace of collection so much that many
locations are missed. At a pace and volume that was too much for the county's
fleet to manage, our team, along with colleagues from IBM Research-Ireland and IBM Watson, signed on to help.

IBM Research-Africa's Tierra Bills working with Nairobi city officials.

We applied our expertise in big data, analytics and
mobile technology to design a first-of-a-kind solution to tackle these
problems. Using an unconventional approach, we developed a pilot program in
which the benefit was two-fold: by mounting smart devices to the city's waste
management trucks, we could, for the first time, collect important data about
the fleet, trucks and drivers, while also tracking problems on the roadways.

We became immersed in the work, driving our own cars, sensor devices in-hand, up and down the streets of Nairobi's
South Ward C to test and learn how the data was being collected - comparing
the readings to what was actually happening in real time. Once we fine-tuned
the smart devices, the sensor were installed onto 10 trucks, or as we call them, our
"data-collecting ants," gathering and transmitting data, via Safaricom's mobile network, about the
truck's location, altitude, speed, acceleration, orientation, vibration levels, among other readings.

The application sends data in near real-time to our backend where it's processed, then relevant information is sent to a tablet
or mobile device that the fleet supervisor can monitor. It provides
analytics-based indicators and alerts to improve performance of the entire
fleet, as well as maintenance of individual vehicles; assist the supervisory team
on driver and truck tracking; and provide information about the storage depots
and facilities within the city. The insights will help the city design a more
efficient system for picking up waste, so that, for example, areas that are
less frequently attended to can be serviced, ultimately helping to improve the
ensuing issues of poor sanitation and theft.

In the bigger picture, road blockages, accidents,
detours, even unmarked speed bumps and hazardous potholes, could be reported back to city
officials for tracking and response. Besides the improvements to waste
management, the ultimate goal is to condition Nairobi's streets and related
urban infrastructure more efficiently. We hope that the overall economic and
social impact of this work will be realized by all residents of Nairobi, and
that our solution can scale to surrounding cities, regions and, foundationally,
across industries.

7.15.2015

My team at IBM’s research lab in the
Silicon Valley just discovered a new class of “self-healing” organogels that have
unique recyclable properties – they are the first class of chemically-crosslinked
gels that can be cooled to a solid, but then re-heated back to a liquid state. Imagine
filling a mold with this liquid material, cooling it and discovering there was
a mistake – with this material and its dynamic properties, we can start over until
we get the desired shape, and then cure it to a permanent, hardened object. We
describe how this process works in the paper, Melt-Processable
Dynamic-Covalent Poly(Hemiaminal) Organogels as Scaffolds for UV-Induced
Polymerization, published in the journal, Advanced Materials.

What is a gel?

Gels are
a peculiar family of materials. They exhibit properties between solids and
liquids, and are composed of long polymer chains which link together and can
trap some other smaller molecules. They are like a tiny (think nanoscale) fishing
net that can retain liquids. The small molecules, which are trapped in the
organogels that we developed, are monomers (the initial molecules which are
used to prepare polymers). In our experiment, we also added some molecules called initiators in the gels, which under UV light transform the monomers into polymers. Thus, our gels have unique properties that allow them to behave at first like jello but after UV exposure become hard like plastic.

The
elasticity of our organogel on display

After dozens of tests to measure the strength of the gels and figuring out the right compositions to obtain these properties, we created a modified gel that could melt at higher temperatures (80C) but recover its gel-like behavior when cooled down to 20C. The result is the first type of gel that could be molded, unmolded, and remolded several times before reaching that perfect final shape fixed by UV exposure.

Think of our gels like caulk used to repair cracks in objects, but liquid enough to penetrate into small cracks, and solid enough not to leak. A subsequent UV-curing step would allow for the material filling the crack to solidify and for the object to recover properties close to its original shape and strength.
In the future, those gels could be used as a material for 3D-printing. If you think about today’s 3D-printing process, it requires layers of polymers stacked
on top of each other. This leads to imperfect shapes that can have weakly bonded interfaces between its layers. Our new “self-healing”
materials are not only fluid enough to be printed but also solid enough to hold
their shape. By precisely controlling the printing temperature, we could
ultimately get rid of the layers’ interface problem.

IBM’s gel
(B), once heated, returns to its original state demonstratingrecyclable, remoldable properties. A typical gel (A) retains its form with heat.

A lab legacy

This gel
discovery stems from work by IBM scientists Jim Hedrick and Jeannette Garcia
two years ago, when they discovered how to synthesize industrial
polymers. We applied this chemistry to our gels using computational
chemistry – co-author and IBMer Gavin Jones simulated the affinity our organogels’
crosslinks with the different monomers we used, and showed that they bound in
a similar way as the original molecules used by Jim and Jeannette. Our team’s
rheology expert, Nancy Zhang, also measured the gel’s ability to flow, and its strength.
Her data explained how to perceive the gel’s hardness and softness, and also
proved that the gel could be remolded multiple times before losing its strength.